We propose BIGKnock (BIobank-scale Gene-based association test via Knockoffs), a computationally efficient gene-based testing approach for biobank-scale data, that leverages long-range chromatin interaction data, and performs conditional genome-wide testing via knockoffs. BIGKnock can prioritize causal genes over proxy associations at a locus. We apply BIGKnock to the UK Biobank data with 405,296 participants for multiple binary and quantitative traits, and show that relative to conventional gene-based tests, BIGKnock produces smaller sets of significant genes that contain the causal gene(s) with high probability. We further illustrate its ability to pinpoint potential causal genes at [Formula: see text] of the associated loci.
BIGKnock: fine-mapping gene-based associations via knockoff analysis of biobank-scale data.
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作者:Ma Shiyang, Wang Chen, Khan Atlas, Liu Linxi, Dalgleish James, Kiryluk Krzysztof, He Zihuai, Ionita-Laza Iuliana
| 期刊: | Genome Biology | 影响因子: | 9.400 |
| 时间: | 2023 | 起止号: | 2023 Feb 13; 24(1):24 |
| doi: | 10.1186/s13059-023-02864-6 | ||
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